Factor analysis of metabolic syndrome using directly measured insulin sensitivity: The Insulin Resistance Atherosclerosis Study

Insulin resistance, insulin response, and obesity as indicators of metabolic risk

CONTEXT

Insulin resistance (IR) and obesity, especially abdominal obesity, are regarded as central pathophysiological features of a cluster of cardiovascular risk factors (CVRFs), but their relative roles remain undefined. Moreover, the differential impact of IR viz. insulin response has not been evaluated.

OBJECTIVE

The objective of this study was to dissect out the impact of obesity, abdominal obesity, and IR/insulin response on CVRF.

DESIGN

This was a cross-sectional study.

SETTING

The study was conducted at 21 research centers in Europe.

SUBJECTS

The study included a cohort of 1308 nondiabetic subjects [718 women and 590 men, age 30-60 yr, body mass index (BMI) 17-44 kg.m(-2)].

MAIN OUTCOME MEASURES

We measured IR (by a standardized euglycemic insulin clamp), waist girth, insulin response to an oral glucose tolerance test, and major CVRF, and analyzed their associations by multivariate models and factor analysis.

RESULTS

BMI was positively related to all CVRFs. Waist circumference was related to higher blood pressure and serum triglycerides and lower high-density lipoprotein-cholesterol, IR to reduced glucose tolerance, higher free fatty acids, triglyceride and low-density lipoprotein-cholesterol, and lower high-density lipoprotein-cholesterol, and insulin response to higher heart rate, blood pressure and fasting glucose, and the same dyslipidemic profile as IR (P < or = 0.05 for all). By factor analysis, three main factors (related to IR, age, and fatness, respectively) appeared to underlie this pattern of associations. Each of BMI, waist girth, IR, and insulin response was independently associated with total CVRF load (all P < 0.001).

CONCLUSIONS

When IR, fat mass and distribution, and insulin response are measured simultaneously in a large cohort, no one factor stands out as the sole driving force of the CVRF cluster, each being associated with one or more physiological pathways according to known cause-effect relationships.

Obstructive sleep apnea syndrome is associated with some components of metabolic syndrome

BACKGROUND

Obesity, hypertension, dyslipidemia, and hyperglycemia are prevalent in obstructive sleep apnea syndrome (OSAS). Metabolic syndrome, however, is defined by visceral fat obesity plus at least two of these factors. However, whether OSAS contributes to the development of metabolic syndrome has not been defined. We investigated whether the components of metabolic syndrome were associated with OSAS in nonobese patients.

METHODS

We investigated the occurrence of hypertension, dyslipidemia, and hyperglycemia in 42 men with OSAS and 52 men without OSAS matched for age, body mass index (BMI), and visceral fat accumulation.

RESULTS

Although serum levels of triglycerides, high-density lipoprotein cholesterol, and diastolic BP did not differ significantly between the two groups, fasting blood glucose (111 +/- 6 mg/dL vs 93 +/- 3 mg/dL) [mean +/- SE] and the percentage of hypertensive patients (45% vs 15%) were significantly higher in the group with OSAS. In addition, a significantly higher percentage of patients with OSAS (19% vs 4%) had at least two of the following: hypertension, hyperglycemia, and dyslipidemia. Logistic regression analysis showed that the apnea-hypopnea index value was the predictor of number of metabolic syndrome parameters such as hypertension, hyperglycemia, and dyslipidemia, while BMI and lowest arterial oxygen saturation during sleep did not.

CONCLUSION

Independent of visceral fat obesity, OSAS was associated with hypertension, dyslipidemia, and hyperglycemia. It is possible that OSAS may predispose even nonobese patients to the development of metabolic syndrome.

Metabolic Syndrome: An Evolving Threat in the Genesis of Coronary Artery Disease

Cardiovascular disease is an escalating worldwide health problem. Effective tools to predict and prevent its development and progression are needed. Correctly diagnosing the metabolic syndrome, which identifies people at higher risk for developing diabetes mellitus and cardiovascular disease, may be valuable in guiding treatment and prevention of these major disorders. Several important definitions of the metabolic syndrome have been proposed. The authors discuss these definitions and how they vary in terms of their relationship to incident cardiovascular disease, type 2 diabetes mellitus, and surrogate markers of atherosclerosis. Establishing clarity on what is meant by the metabolic syndrome and agreement as to its underlying basis is needed to reach consensus between the many different definitions that have been proposed. This is particularly the case if it is to become a useful adjunct in clinical practice to identify those who may benefit from more intensive lifestyle interventions and more detailed short-term risk assessments.

Carotid atherosclerosis associated to metabolic syndrome but not BMI in healthy menopausal women

BACKGROUND

Obesity and the metabolic syndrome (MS) frequently coexist. Both are apparently associated to cardiovascular disease. However, the contribution of obesity to cardiovascular risk, independent of the presence of the metabolic syndrome, remains controversial. The purpose of this study was to investigate whether the subclinical carotid atherosclerosis prevalence is different in obese postmenopausal women with and without the metabolic syndrome.

METHODS

On the basis of consecutive recruitment, 313 postmenopausal women underwent a clinical, biochemical and ultrasound characterization. Women affected by cardiovascular disease or diabetes were excluded from the study.

RESULTS

Among enrolled women the metabolic syndrome and body mass index (BMI) resulted strongly associated, but only metabolic syndrome was associated with carotid atherosclerosis, a well-known marker of cardiovascular disease. Similarly, increases in BMI unit (normal to overweight to obese) were not associated with carotid atherosclerosis whereas metabolic status (normal to metabolic syndrome) conferred an approximate three-fold adjusted odds of carotid atherosclerosis.

CONCLUSIONS

The metabolic syndrome but not obesity is associated to carotid atherosclerosis in postmenopausal women. Although it remains prudent to recommend weight loss in overweight and obese women, evaluation and control of metabolic risk factors should be considered the main goal to prevent cardiovascular and cerebrovascular disease.

Mechanisms of the components of the metabolic syndrome that predispose to diabetes and atherosclerotic CVD

The metabolic syndrome represents a summation of obesity-driven risk factors for atherosclerotic CVD and type 2 diabetes. Definitions of the syndrome vary but in general agree closely in identifying subjects. The relationships between the metabolic syndrome and atherosclerotic CVD and diabetes also vary, with relative risks of approximately 1.5-3.0 and approximately 3.0-5.0 respectively. Insulin resistance appears to explain much of the pathophysiology of the syndrome. Both increased fatty acid flux and an excess of circulating pro-inflammatory cytokines are likely mediators. With increased waist circumference, increases in fatty acid delivery to the liver result in higher rates of hepatic glucose production and increases in the secretion of apoB-containing lipoproteins. Concomitant changes in HDL ensue, including a replacement of the cholesterol content with TAG, an accelerated clearance from the plasma and thus a reduced number of HDL particles. Typically also present are increases in small dense LDL. Hypertension in part relates to the insulin resistance, but may involve other mechanisms. Impaired fasting glucose often relates to defects in insulin secretion in addition to insulin resistance, and probably more than any other component of the syndrome predicts the increased incidence of type 2 diabetes. Although not included in the diagnostic criteria, increases in pro-inflammatory cytokines and pro-thrombotic factors, in addition to decreases in plasma adiponectin, may also contribute to the increased incidence of atherosclerotic CVD and diabetes. In general, the greater the number of metabolic syndrome components, the greater the risk for these outcomes. The cytokines and pro-thrombotic factors also appear to contribute.

Do low levels of circulating adiponectin represent a biomarker or just another risk factor for the metabolic syndrome?

The metabolic syndrome is currently defined by various combinations of insulin resistance, obesity, dyslipidaemia and hypertension. The tendency for these risk factors to appear simultaneously suggests a single aetiologic basis. A low level of circulating adiponectin is associated with the appearance of each metabolic syndrome risk factor. The following review summarizes a large body of evidence that suggests a low level of circulating adiponectin represents an independent risk factor and a possible biomarker for the metabolic syndrome. An association between the metabolic syndrome and low adiponectin supports the view that the development of the metabolic syndrome may be triggered by a single underlying mechanism. Clinical studies in the future may show that a low level of circulating adiponectin is a primary biomarker for a specific cluster of metabolic syndrome risk factors rather than all the possible combinations of risk factors currently used to identify the metabolic syndrome. The significance of low circulating adiponectin in risk assessment models should ultimately be compared against insulin resistance, obesity, dyslipidaemia, hypertension and other metabolic syndrome risk factors presently under consideration. Adiponectin can be measured reliably in a clinical setting; circulating values of adiponectin do not fluctuate on a diurnal basis as much as insulin, glucose, triglycerides or cholesterol and only 2-4 microl of blood are currently needed for its measurement.

In addition to obesity and insulin resistance, microalbuminuria and diminished insulin secretion are linked with the metabolic syndrome in community-dwelling nondiabetic Taiwanese subjects

Although insulin resistance and obesity are currently considered primary factors underlying development of the metabolic syndrome, microalbuminuria and inadequate insulin secretion may also be involved. The present study is the first to examine intercorrelations among these factors in a community-based Taiwanese population. An epidemiological survey of chronic diseases conducted in 1996 was utilized to evaluate 1340 community-dwelling, nondiabetic adults. Principal component factor analyses involving varimax orthogonal rotation of transformed continuously distributed variables were performed. Sex-specific factor analyses yielded four separate factors in women (obesity/insulin resistance, lipid, blood pressure and insulin resistance/secretion factors) and three in men (obesity/insulin resistance/secretion, lipid and blood pressure factors). For men the corrected insulin response clustered with obesity, and insulin resistance loaded on the same factor, explaining 31% of variance; however, microalbuminuria was closely linked with blood pressure variables, and the corrected insulin response loaded on the same factor, explaining 13.2% of variance. Obesity and insulin resistance were confirmed as central anomalies of all features of the metabolic syndrome. The observed linkage of impaired beta-cell function and microalbuminuria with the metabolic syndrome should facilitate prediction of the onset of cardio-vasculo-metabolic disorders. Inadequate beta-cell function and microalbuminuria are plausible components of the metabolic syndrome in Taiwanese subjects.

Obesity, metabolic syndrome and sleep apnoea: all pro-inflammatory states

Obesity is associated with significant morbidity and mortality and is increasing in prevalence worldwide. Associated conditions include insulin resistance (IR), diabetes, hypertension and dyslipidaemia; a clustering of these has recently been termed as metabolic syndrome. Weight gain is a major predictor of the metabolic syndrome with waist circumference being a more sensitive indicator than body mass index as it reflects both abdominal subcutaneous adipose tissue and visceral adipose tissue (VAT). VAT has more metabolic activity and secretes a number of hormones and pro-inflammatory cytokines which are linked with the metabolic abnormalities listed above. Central obesity also increases the risk of obstructive sleep apnoea syndrome (OSAS), where the sleep disordered breathing may also independently lead to/or exacerbate IR, diabetes and cardiovascular risk. The contribution of OSAS to the metabolic syndrome has been under-recognized. The putative mechanisms by which OSAS causes or exacerbates these other abnormalities are discussed. We propose that activation of nuclear factor kappa B by stress hypoxia and/or by increased adipokines and free fatty acids released by excess adipose tissue is the final common inflammatory pathway linking obesity, OSAS and the metabolic syndrome both individually and, in many cases, synergistically.

Impact of clinical characteristics of individual metabolic syndrome on the severity of insulin resistance in Chinese adults

The impact the metabolic syndrome (MetS) components on the severity of insulin resistance (IR) has not been reported. We enrolled 564 subjects with MetS and they were divided into quartiles according to the level of each component; and an insulin suppression test was performed to measure IR. In males, steady state plasma glucose (SSPG) levels in the highest quartiles, corresponding to body mass index (BMI) and fasting plasma glucose (FPG), were higher than the other three quartiles and the highest quartiles, corresponding to the diastolic blood pressure and triglycerides, were higher than in the lowest two quartiles. In females, SSPG levels in the highest quartiles, corresponding to the BMI and triglycerides, were higher than in all other quartiles. No significant differences existed between genders, other than the mean SSPG levels in males were greater in the highest quartile corresponding to BMI than that in the highest quartile corresponding to HDL-cholesterol levels. The factor analysis identified two underlying factors (IR and blood pressure factors) among the MetS variables. The clustering of the SSPG, BMI, triglyceride and HDLcholesterol was noted. Our data suggest that adiposity, higher FPG and triglyceride levels have stronger correlation with IR and subjects with the highest BMI have the highest IR.

Impaired Glucose Tolerance and Impaired Fasting Glucose Share Similar Underlying Pathophysiologies

Both impaired glucose tolerance (IGT) and impaired fasting glucose (IFG) are pre-diabetic states. IGT was defined as having normal fasting plasma glucose (< 6.1 mmol/l) and abnormal 2-hr post-challenge plasma glucose. IFG was defined as having abnormal fasting plasma and normal 2-hr post-challenge plasma glucose (< 7.8 mmol/l). To explore whether these two abnormalities share similar underlying pathophysiologies, we evaluated risk factors of IGT and IFT using the models of factor analysis. The present study included 107 subjects with IGT and 52 with IFG. An oral glucose tolerance test and insulin suppression test, which could quantify insulin resistance, were performed on separate days. The risk factors include waist-to-hip ratio (WHR), triglycerides, high-density lipoprotein (HDL)-cholesterol, blood pressure, and fasting plasma glucose, which are associated with metabolic syndrome and insulin resistance. Factor analysis is a commonly used statistical method that could reduce a large number of risk factors into smaller numbers of groups, also called dimension. Accordingly, the complicated data could be interpreted more easily, since the related risk factors are grouped in one dimension. The results showed that the risk factors of IGT and IFG have similar grouping patterns. Triglyceride, insulin resistance, and HDL-cholesterol were grouped in one dimension (the lipid dimension), while WHR, mean blood pressure and fasting plasma glucose were grouped in another dimension (the metabolic dimension). In conclusion, except for WHR, the grouping patterns of the components in both IGT and IFG were nearly identical. These results suggest that IGT and IFG may share similar pathophysiologies.

Metabolic syndrome is common among middle-to-older aged Mediterranean patients with rheumatoid arthritis and correlates with disease activity: a retrospective, cross-sectional, controlled, study

OBJECTIVES

Patients with rheumatoid arthritis have an increased risk for cardiovascular disease (CVD). The prevalence of metabolic syndrome (MetS)-a major contributor to CVD-in a cohort of patients with rheumatoid arthritis and its relationship with rheumatoid arthritis related factors is investigated here.

METHODS

200 outpatients with rheumatoid arthritis (147 women and 53 men), with a mean (standard deviation (SD)) age of 63 (11) years, and 400 age and sex-matched controls were studied. MetS was assessed according to the adult treatment panel III criteria and rheumatoid arthritis disease activity by the disease activity score of 28 joints (DAS28). A standard clinical evaluation was carried out, and a health and lifestyle questionnaire was completed.

RESULTS

The overall prevalence of MetS was 44% in patients with rheumatoid arthritis and 41% in controls (p = 0.5). Patients with rheumatoid arthritis were more likely to have low high-density lipoprotein cholesterol compared with controls (p = 0.02), whereas controls were more likely to have increased waist circumference or raised blood pressure (p = 0.001 and 0.003, respectively). In multivariate logistic regression analysis adjusting for demographics and rheumatoid arthritis treatment modalities, the risk of having moderate-to-high disease activity (DAS28>3.2) was significantly higher in patients with MetS compared with those with no MetS components (OR 9.24, 95% CI 1.49 to 57.2, p = 0.016).

CONCLUSION

A high, albeit comparable to the control population, prevalence of MetS was found in middle-to-older aged patients with rheumatoid arthritis. The correlation of rheumatoid arthritis disease activity with MetS suggests that the increased prevalence of coronary heart disease in patients with rheumatoid arthritis may, at least in part, be attributed to the inflammatory burden of the disease.

Metabolic syndrome components in Indian migrants with type 2 diabetes. A matched comparative study

OBJECTIVE

To study the metabolic syndrome (MS) in Indian subjects with type 2 diabetes (T2D) in comparing them with controls from the Indian community and from the general population.

METHOD

An adapted definition of MS by the Third report of the National Cholesterol Education Program's Adult Treatment Panel III was used. We defined three groups matched for sex and age (+/-5 years). Non parametric tests for comparison of matched samples and conditional logistic regression were used.

RESULTS

We selected 71 Indians with T2D (group 1) and two control groups with fasting blood glucose<6.1 mmol/L: 71 Indians (group 2) and 213 subjects from the general population (group 3). Patients were 24 to 76 years-old and each group contained 56% men. Globally, MS was identified in 77% of the group 1 when diabetes was taken into account. When diabetes was excluded there were 47% of MS in group 1, 18% in group 2 and 16% in group 3. The clusters of four factors (hypertension, large waist circumference, hypertriglyceridemia and Low HDL-C) were more common in Indians. The most frequent factors were hypertriglyceridemia and large waist circumference in Indians. Indians with T2D had a 5-fold higher risk of MS than the general population group, OR (95% CI): 4.93 (2.71 - 8.97); P<0.001.

CONCLUSION

The high frequency of MS and of hypertriglyceridemia in Indians with T2D highlights the need for screening and management of MS in this population facing a high cardiovascular risk.

Combined cardiovascular risk factors and outcome: NIPPON DATA80, 1980-1994

BACKGROUND

To examine the prognostic significance of the high-risk group with combined cardiovascular risk factors in the Japanese, we analyzed the relationship between the high-risk group with combined risks and coronary heart disease (CHD) and stroke mortality using the NIPPON DATA80 database.

METHODS AND RESULTS

At baseline in 1980, those of age>or=30 years were randomly selected and 4,144 men and 5,318 women without CHD and/or stroke at baseline were followed for 14 years. The cutoff values for risk components obtained heuristically by Cox analysis were hypertension (systolic>or=130, or diastolic>or=85 mmHg, or on antihypertensive drugs), hypercholesterolemia (total cholesterol>or=200 mg/dl), hyperglycemia (>or=130 mg/dl, or self-reported diabetes) and obesity (body mass index>or=27 kg/m2). Subjects were divided into 3 groups (0, 1-2 and 3-4 risks). Compared with those men in the risk 0 group, the hazard ratios in men in the risk 3-4 for CHD mortality was 8.04 (95% confidence interval: 1.03-62.6), and the stroke mortality was 5.06 (1.53-16.7). In women, no statistically significant difference was found due to a lesser number of events.

CONCLUSION

The high-risk group with combined risk factors is important risk for Japanese men.

A pathophysiological approach to metabolic syndrome using factor analysis in an adult Romanian population

The aim of the study was to examine the role of insulin resistance in etiopathogenesis of metabolic syndrome in an adult Romanian population using exploratory factor analysis. We analyzed 228 non-diabetic subjects randomized in respect to the age and sex distribution of the general population. For each patient, age, sex, body mass index (BMI), systolic and diastolic blood pressure (SBP, DBP), HDL-cholesterol (HDL), plasma triglycerides (TG), fasting plasma glucose (FPG) and fasting insulin were obtained. Factor analysis was performed using principal component analysis, with Varimax rotation of the major determinants of metabolic syndrome. Mean age was 48.9 +/- 12.7 years; 107 (46.9%) were men and 121 (53.1%) women. We found three major factors, which are correlated with metabolic syndrome and may explain its variance. Factor 1 comprises SBP and DBP in men and SBP, DBP and BMI in women. Factor 2 comprises BMI, HDL, TG and FPG in men and BMI, TG and FPG in women. Factor 3 comprises fasting insulin in men and fasting insulin, TG and HDL in women. The finding of more than one factor suggests that insulin resistance is not the only pathophysiological mechanism involved. These factors appear to work independently of each other in men, but they intersect in women, suggesting that the pathophysiology of metabolic syndrome may be different in women compared with men.

The metabolic basis of atherogenic dyslipidemia

Atherogenic dyslipidemia is one of the major components of the metabolic syndrome, a complex cluster of several risk factors within a single patient that according to the National Cholesterol Education Program (NCEP) Adult Treatment Panel III includes at least 3 of the following: large waist circumference, elevated triglyceride levels, low levels of high-density lipoprotein cholesterol (HDL-C), hypertension, and elevated fasting glucose levels, which are directly related to the incidence of coronary heart disease. Atherogenic dyslipidemia clinically presents as elevated serum triglyceride levels, increased levels of small dense low-density lipoprotein (sdLDL) particles, and decreased levels of HDL-C. An important component of atherogenic dyslipidemia is central obesity, which is defined as increased waist circumference and has recently been identified as a chief predictor of the metabolic syndrome in certain patients. Another recent study found that both body mass index and waist circumference were highly predictive of eventual development of the metabolic syndrome. Because atherogenic dyslipidemia usually precedes the clinical manifestation of the metabolic syndrome, strategies to treat it are the focus of pharmacologic intervention. For example, the 3-hydroxy-3-methylglutaryl coenzyme-A reductase inhibitors, commonly known as statins, benefit hypercholesterolemic patients who have atherogenic dyslipidemia that is associated with the metabolic syndrome. Pioglitazone, an antidiabetic agent that acts primarily by decreasing insulin resistance, improves sensitivity to insulin in muscle and adipose tissue and inhibits hepatic gluconeogenesis. Pioglitazone improves glycemic control while reducing circulating insulin levels. The investigational agent, rimonabant--a centrally and peripherally acting, selective cannabinoid type-1 receptor blocker--is the first therapy developed for managing several cardiovascular risk factors at one time. Rimonabant has shown promise in attacking atherogenic dyslipidemia from several vantage points by affecting glucose, HDL-C, triglycerides, and waist circumference in patients who are prone to atherogenic dyslipidemia.

Cardiovascular risk reduction

A case on cardiovascular risk reduction is presented. Multiple cardiovascular risks (dyslipidemia, hypertension, and diabetes) are addressed. Management of the metabolic syndrome and appropriate testing for the newer cardiovascular marker, C-reactive protein, are also discussed. The case emphasizes the importance of patient education about chronic disease states, which are often asymptomatic.

Evaluation and comparison of models of metabolic syndrome using confirmatory factor analysis

The aim of this study was to evaluate and compare three competing models of the underlying factor structure of metabolic syndrome using confirmatory factor analysis (CFA). Data from the Insulin Resistance Atherosclerosis Study (IRAS) was used, which has previously been evaluated using principal components analysis (PCA). The three models that were evaluated consisted of oblique and orthogonal two-factor models with hypothesized underlying "metabolic" and "blood pressure" factors, and a four-factor model theorizing "insulin resistance," "obesity," "lipids," and "blood pressure" as the underlying constructs. Several CFAs were performed using EQS Multivariate Software Version 5.7b with maximum likelihood estimation. The results showed that the four-factor model yielded significantly better data-model fit than two-factor models, with a comparative fit index of 0.963, and standardized root mean square residual of 0.036. Factors exhibited good construct reliability and variance extracted estimates except for the lipids factor. We concluded that the four-factor model of metabolic syndrome was the most plausible model among the three competing models.

Degradation in insulin sensitivity with increasing severity of the metabolic syndrome in obese postmenopausal women

AIM

We investigated the relationship between insulin sensitivity and the graded increase in the number of features of the metabolic syndrome in a cross-sectional sample of obese postmenopausal women. We hypothesized that insulin sensitivity would deteriorate with an increased number of metabolic syndrome phenotypes.

METHODS

Insulin sensitivity was measured in 75 obese postmenopausal women (age: 57.3 +/- 5.3 years; BMI: 32.8 +/- 4.5 kg/m2) by using both the hyperinsulinaemic-euglycaemic clamp and the homeostasis model assessment (HOMA-IR). Features of the metabolic syndrome included visceral fat (>130 cm2), HDL-cholesterol (<1.29 mmol/l), fasting triglycerides (> or =1.7 mmol/l), blood pressure (> or =130/> or =85 mmHg) and fasting glucose (> or =6.1 mmol/l). Participants were classified into three categories based on the presence of metabolic syndrome phenotypes: 0-1 vs. 2 vs. > or =3 features of the metabolic syndrome.

RESULTS

We found that insulin sensitivity decreased in a graded fashion (12.19 +/- 3.2 vs. 11.80 +/- 2.3 vs. 9.29 +/- 2.6 mg/min/FFM) and HOMA-IR increased in a similar manner (2.95 +/- 1.1 vs. 3.28 +/- 1.3 vs. 4.65 +/- 2.2), as the number of features of the metabolic syndrome increased from 0-1 to > or =3. When insulin sensitivity was statistically adjusted for visceral fat (as measured by computed tomography) and plasma triglycerides, the differences among groups were abolished.

CONCLUSIONS

These findings suggest that a decreased insulin sensitivity is associated with increased features of the metabolic syndrome in obese postmenopausal women and that visceral fat as well as plasma triglyceride accumulation might be potential mediators of this relationship.

Adult Treatment Panel III 2001 but not International Diabetes Federation 2005 criteria of the metabolic syndrome predict clinical cardiovascular events in subjects who underwent coronary angiography

OBJECTIVE

The International Diabetes Federation (IDF) has recently established a worldwide consensus definition of the metabolic syndrome. No prospective data are available on the cardiovascular risk associated with this new metabolic syndrome definition.

RESEARCH DESIGN AND METHODS

In a prospective study of 750 coronary patients, we recorded vascular events over 4 years.

RESULTS

From our patients, 37.3% (n = 280) had the metabolic syndrome according to the Adult Treatment Panel III (ATPIII) definition and 45.5% (n = 341) according to the IDF definition. The metabolic syndrome as defined by the ATPIII criteria significantly predicted vascular events (adjusted hazard ratio 1.745 [95% CI 1.255-2.427]; P = 0.001), but the metabolic syndrome as defined by IDF criteria did not (1.189 [0.859-1.646]; P = 0.297). Accordingly, event-free survival was significantly lower among patients who fulfilled the ATPIII but not the IDF criteria than among those who met the IDF but not the ATPIII criteria (P = 0.012). The metabolic syndrome as defined by ATPIII criteria remained significantly predictive of vascular events after adjustment for type 2 diabetes but not after additional adjustment for the metabolic syndrome components high triglycerides and low HDL cholesterol. These lipid traits in turn proved significantly predictive of vascular events even after adjustment for the metabolic syndrome.

CONCLUSIONS

The ATPIII definition of the metabolic syndrome confers a significantly higher risk of vascular events than the IDF definition. However, among angiographied coronary patients, even the ATPIII definition of the metabolic syndrome does not provide prognostic information beyond its dyslipidemic features.

The metabolic syndrome and changing relationship between blood pressure and insulin with age, as observed in Aboriginal and Torres Strait Islander peoples

AIMS

To determine the prevalence of the metabolic syndrome (MS) among Aboriginal and Torres Strait Islander peoples. A further objective was to investigate the relationships between fasting insulin and blood pressure (BP) within these groups with increasing age.

METHODS

A cross-sectional population-based study included 369 Torres Strait Islanders (residing in Torres Strait and Far North Queensland), and 675 Aborigines from central Australia. Data necessary for classification of MS was collected, including fasting and 2-h glucose and insulin, urinary albumin and creatinine, anthropometric measurements, BP, serum lipids.

RESULTS

The ATPIII criteria classified 43% of Torres Strait Islanders and 44% of Aborigines with MS, whereas 32 and 28%, respectively, had the MS according to WHO criteria. Agreement between the two criteria was only modest (kappa coefficient from 0.28 to 0.57). Factor analyses indicated no cluster including both insulin and BP in either population. Significant correlations (P < 0.05) [adjusted for gender, body mass index (BMI) and waist circumference] were observed between BP and fasting insulin: a positive correlation for Torres Strait Islanders aged 15-29 years, and an inverse correlation for Aborigines aged 40 years and older.

CONCLUSION

Torres Strait Islanders and Aborigines had very high prevalences of the MS. Specific population characteristics (high prevalences of central obesity, dyslipidaemia, renal disease) may make the WHO definition preferable to the ATPIII definition in these population groups. The poor agreement between criteria suggests a more precise definition of the metabolic syndrome that is applicable across populations is required. This study showed an inverse relationship with age for the correlation of BP and fasting insulin.

Two major QTLs and several others relate to factors of metabolic syndrome in the family blood pressure program

Genome-wide variance components linkage analysis was performed on 4 latent factors underlying metabolic syndrome derived from 10 risk factors. The latent factors represent obesity and insulin, blood pressure, lipids and insulin, and central obesity. The metabolic syndrome factor scores were derived in 4 ethnic groups recruited in 3 Networks of the Family Blood Pressure Program: GENOA (blacks, Hispanics, and whites), HyperGEN (blacks and whites), SAPPHIRe (Asians). Heritabilities of metabolic syndrome factors ranged from 66% for obesity and insulin to 11% for blood pressure factor. We observed higher heritabilities for obesity and insulin, and lipids and insulin, whereas those for blood pressure and central obesity were smaller. Linkage analysis detected two major quantitative trait loci. One of them linked to the obesity and insulin factor with a lod score of 3.94 (P=0.00001, marker GATA11A06, D18S53, 41.24 cM) at marker positions linkage (lod 4.71, at 46.84 cM at 1-cM-apart distances linkage), located on chromosome 18p11.21 in GENOA black. The other linked to the blood pressure factor with a lod score of 3.22 (P=0.000059, marker GATA49C09, D17S1290, 82 cM) at marker positions linkage (lod 3.56, at 84.63 cM for 1 cM apart distances linkage) located on chromosome 17q23.1 in Hispanics. These quantitative trait loci, together with 4 additional ones with lod scores >2.5, and 30 additional ones with lod score >1.7, offer hope for dissecting the genetic architecture of metabolic syndrome with beneficial implications for molecular diagnosis, prognosis, and in potential medical intervention.

The metabolic syndrome: time for a critical appraisal: joint statement from the American Diabetes Association and the European Association for the Study of Diabetes

The term "metabolic syndrome" refers to a clustering of specific cardiovascular disease (CVD) risk factors whose underlying pathophysiology is thought to be related to insulin resistance. Since the term is widely used in research and clinical practice, we undertook an extensive review of the literature in relation to the syndrome's definition, underlying pathogenesis, and association with CVD and to the goals and impact of treatment. While there is no question that certain CVD risk factors are prone to cluster, we found that the metabolic syndrome has been imprecisely defined, there is a lack of certainty regarding its pathogenesis, and there is considerable doubt regarding its value as a CVD risk marker. Our analysis indicates that too much critically important information is missing to warrant its designation as a "syndrome." Until much needed research is completed, clinicians should evaluate and treat all CVD risk factors without regard to whether a patient meets the criteria for diagnosis of the "metabolic syndrome."

The metabolic syndrome: time for a critical appraisal. Joint statement from the American Diabetes Association and the European Association for the Study of Diabetes

BACKGROUND

The term 'metabolic syndrome' refers to a clustering of specific cardiovascular disease (CVD) risk factors whose underlying pathophysiology is thought to be related to insulin resistance.

METHODS

Since the term is widely used in research and clinical practice, we undertook an extensive review of the literature in relation to the syndrome's definition, underlying pathogenesis, association with cardiovascular disease and to the goals and impact of treatment.

DISCUSSION

While there is no question that certain CVD risk factors are prone to cluster, we found that the metabolic syndrome has been imprecisely defined, there is a lack of certainty regarding its pathogenesis, and there is considerable doubt regarding its value as a CVD risk marker. Our analysis indicates that too much critically important information is missing to warrant its designation as a 'syndrome'.

CONCLUSION

Until much-needed research is completed, clinicians should evaluate and treat all CVD risk factors without regard to whether a patient meets the criteria for diagnosis of the 'metabolic syndrome'.

Calculating Insulin Resistance in the Primary Care Setting: Why Should We Worry about Insulin Levels in Euglycemic Patients?

PURPOSE

To describe measures that would determine which patients are insulin resistant and at risk for the metabolic syndrome and its sequelae cardiovascular diseases (CVD) and to analyze methods to determine the presence of insulin resistance and the advantages or disadvantages of each.

DATA SOURCES

Review of the multidisciplinary clinical and research literature.

CONCLUSIONS

Insulin resistance occurs early in the trajectory of the metabolic syndrome, making it a prime candidate for timely interventions to reduce risk for both type 2 diabetes and CVD. Therefore, prompt recognition of insulin resistance prior to the development of the full metabolic syndrome, type 2 diabetes, and/or CVD may assist in the prevention of morbidity and premature mortality. Likewise, because many insulin-resistant patients belong to minority racial groups (i.e., African American, Hispanic, Native American, or Pacific Islanders), early identification may have a positive impact on the reduction of cardiovascular health disparities.

IMPLICATIONS FOR PRACTICE

Documenting the presence of insulin resistance will assist the practitioner to determine if a low-risk patient is in jeopardy for development of type 2 diabetes and/or CVD. Early cardiovascular risk identification is important to clinical practice as it allows more time for the practitioner to counsel patients for the essential planning needed to make lifestyle changes.

Obesity, Insulin Resistance, and the Metabolic Syndrome

Background— Insulin resistance is strongly associated with obesity and other components of the metabolic syndrome (MS). The relative importance of these components in the determination of endothelial function is unknown. Furthermore, there is conflicting evidence about whether ethnic differences exist in the relative importance of these components in regard to other cardiovascular outcomes. We evaluated the contributions of insulin resistance, obesity, and the other components of the MS to impaired endothelial function.

Methods and Results— The relationships of the MS components (as defined according the National Cholesterol Education Program) and insulin resistance (estimated using the homeostasis model) with endothelium-dependent vasodilation were examined in 42 white and 55 black subjects. Endothelium-dependent vasodilation was assessed as the increment in leg blood flow (measured by thermodilution) after exposure to methacholine chloride. Waist circumference, glucose, blood pressure, and insulin resistance distributions did not differ between ethnic groups; blacks in our sample had higher HDL cholesterol (1.31 versus 1.09 mmol/L; P <0.001) and lower triglyceride levels (1.01 versus 1.37 mmol/L; P =0.005) than white subjects. In the absence of the MS, black subjects exhibited reduced endothelium-dependent vasodilation compared with white subjects ( P =0.005), and both groups demonstrated significantly worse endothelial function when the MS was present (maximal increase in leg blood flow: blacks: 107±9% MS absent, 53±16% MS present; whites: 163±16% MS absent, 54±18% MS absent; P =0.007, MS absent versus present; P =NS for interaction of ethnicity and MS). Multivariable regression analysis examining relationships of endothelial function with the 5 MS components (analyzed as continuous variables) revealed independent relationships only with waist circumference ( P =0.01) and systolic blood pressure ( P =0.02). Waist circumference was no longer independently associated after adding insulin resistance to the modeling ( P =0.02 for log of homeostasis model index of insulin resistance, P =0.02 for systolic blood pressure). Ethnicity still exerted an independent effect on endothelial function after accounting for the above components ( P =0.04 for an additional effect of ethnic status on endothelial function), with an ethnic difference in the effect of insulin resistance on endothelial function ( P =0.046 for interaction of ethnicity and log of homeostasis model index of insulin resistance).

Conclusions— These findings suggest that insulin resistance and systolic blood pressure are the principal determinants of endothelial dysfunction in the MS and that there are ethnic differences in the relative importance of these factors. These differences may imply different benefits from treatments targeting blood pressure or insulin resistance in different ethnic groups.

Comparison of rosuvastatin with atorvastatin, simvastatin and pravastatin in achieving cholesterol goals and improving plasma lipids in hypercholesterolaemic patients with or without the metabolic syndrome in the MERCURY I trial

AIM

The metabolic syndrome (MS) increases the risk of coronary heart disease, yet few data are available on the effects of statin treatment in improving lipid measures in patients with the syndrome. This analysis compares the effects of statin therapy on plasma low-density lipoprotein cholesterol (LDL-C) goal achievement and lipid levels in hypercholesterolaemic patients with or without the MS.

METHODS

The Measuring Effective Reductions in Cholesterol Using Rosuvastatin TherapY I (MERCURY I) trial compared rosuvastatin 10 mg with atorvastatin 10 mg and 20 mg, simvastatin 20 mg and pravastatin 40 mg over 8 weeks in patients with coronary or other atherosclerotic diseases or diabetes who had fasting levels of LDL-C of >or=2.99 mmol/l and triglycerides of <4.52 mmol/l. Modified National Cholesterol Education Program Adult Treatment Panel III (ATP III) criteria for the MS were met by 1342 (43%) of 3140 patients.

RESULTS

LDL-C goal achievement rates and reductions in LDL-C, total cholesterol and non-high-density lipoprotein cholesterol (HDL-C) were similar in patients with and without the MS within statin treatment groups; triglycerides were reduced more and HDL-C tended to be increased more in patients with the MS, as expected. Treatment with rosuvastatin 10 mg was more effective in allowing patients with and without the MS to reach European and ATP III LDL-C goals, compared to atorvastatin 10 mg, simvastatin 20 mg and pravastatin 40 mg (p < 0.0001 for all comparisons); consistently produced greater reductions in LDL-C, total cholesterol and non-HDL-C, compared to these treatments; and produced similar or greater reductions in triglycerides and increases in HDL-C, compared to the other treatments.

CONCLUSIONS

Statin therapy is effective in allowing LDL-C goal achievement and improving the lipid profile in hypercholesterolaemic high-risk patients with the MS. Rosuvastatin 10 mg presents significant advantages in goal achievement and lipid lowering over other statins at commonly used doses in patients both with and without the MS.

Abdominal obesity predicts declining insulin sensitivity in non-obese normoglycaemics: the Insulin Resistance Atherosclerosis Study (IRAS)

AIM

Cross-sectional studies have demonstrated a relationship between obesity and insulin sensitivity (S(I)); however, there is a lack of evidence from longitudinal studies.

METHODS

The Insulin Resistance Atherosclerosis Study (IRAS) estimated S(I) (x10(-4)/min.microU/ml) directly using a frequently sampled intravenous glucose tolerance test with minimal model analysis in 504 normoglycaemic subjects. Partial correlation coefficients (r) were calculated to compare the relationship of change in S(I) from baseline to 5 years later (DeltaS(I)) with baseline waist circumference (waist) as a measure of abdominal obesity and body mass index (BMI) as a measure of overall obesity. Mean DeltaS(I) was -1.06 (SD = 1.85).

RESULTS

Higher baseline waist (r = -0.16; p = 0.0005), but not BMI (r = -0.005; p = 0.91), was associated with (-) DeltaS(I) in models including sex, ethnicity, clinical centre and baseline S(I), BMI, waist, age and physical activity. The waist-DeltaS(I) relationship differed across the levels of baseline BMI, being significant only in normal weight (r = -0.21) and overweight subjects (r = -0.16), but not in obese subjects. DeltaS(I) was correlated with a 5-year change in either obesity measure (Deltawaist: r = -0.22 and DeltaBMI: r = -0.20; p = 0.0001).

CONCLUSIONS

Among non-diabetics, waist circumference was a strong predictor of declining S(I) among lean subjects, a modest predictor among overweight subjects, but was not predictive among obese individuals. Waist circumference should be considered, in addition to BMI, when identifying individuals at high risk of diabetes or the insulin resistance syndrome.

Factor Analysis of Clustered Cardiovascular Risks in Adolescence

Background— Clustering of cardiovascular (CV) risks begins in childhood, yet studies of the factor structure underlying this clustering have focused on adults. The increasing rates of obesity and type 2 diabetes and the growing importance of metabolic syndrome among adolescents make assessment of CV risk clustering even more urgent in this age group.

Methods and Results— Exploratory factor analysis (principal components analysis) was performed with data from 1578 healthy seventh to 12th graders from the Princeton School District Study, a school-based study in Cincinnati, Ohio. Measured CV risks included cholesterol, triglycerides, fasting insulin and glucose, body mass index (BMI), waist circumference, fibrinogen, and blood pressure. Factor analysis yielded 4 uncorrelated factors (adiposity [BMI, waist, fibrinogen, insulin], cholesterol [LDL and total cholesterol], carbohydrate-metabolic [glucose, insulin, HDL cholesterol, triglycerides], and blood pressure [systolic and diastolic blood pressure]). These factors explained approximately 67% of the total variance. A summary cumulative risk scale was derived from factor scores, and high risk was defined as scoring in the top 5%. Although insulin loaded onto both the adiposity and carbohydrate-metabolic factors, obesity was a much stronger correlate of high cumulative risk (odds ratio=19.2; 95% CI, 7.6 to 48.5) than hyperinsulinemia (odds ratio=3.5; 95% CI, 1.8 to 6.8). A sizable proportion (18.5%; n=12) of those who were at high cumulative risk were not at high risk for any of the individual factors.

Conclusions— The patterning of CV risk clustering seen among adults is present in healthy adolescents. Among youth, obesity is the predominant correlate of cumulative risk.

The metabolic syndrome

The metabolic syndrome is a common metabolic disorder that results from the increasing prevalence of obesity. The disorder is defined in various ways, but in the near future a new definition(s) will be applicable worldwide. The pathophysiology seems to be largely attributable to insulin resistance with excessive flux of fatty acids implicated. A proinflammatory state probably contributes to the syndrome. The increased risk for type 2 diabetes and cardiovascular disease demands therapeutic attention for those at high risk. The fundamental approach is weight reduction and increased physical activity; however, drug treatment could be appropriate for diabetes and cardiovascular disease risk reduction.

Components of the metabolic syndrome and carotid atherosclerosis: role of elevated blood pressure

Elevated blood pressure is among the factors that contribute to the metabolic syndrome (MetS). It is not known whether subjects with MetS and elevated blood pressure are at the same cardiovascular risk as subjects with MetS but without elevated blood pressure. To clarify this point, we have evaluated the prevalence of carotid atherosclerosis in subjects with MetS with or without elevated blood pressure. A large population was examined (842 women and 1011 men). Blood pressure, lipids, glucose, and waist were measured by routine methods. Carotid atherosclerosis was evaluated by echo Doppler examination. The prevalence of MetS was 24.4% in women and 28.7% in men. The prevalence of carotid atherosclerosis was 35.1% in women and 37.3% in men (p=NS), and increased with increasing number of MetS components. Age, smoking, and systolic blood pressure (SBP) were associated with the presence of carotid atherosclerosis (logistic model), whereas age, high-density lipoprotein cholesterol, and SBP were associated with the extent of atherosclerosis (linear model). When comparing subjects with an equal number of MetS components, the prevalence of carotid atherosclerosis was significantly higher in subjects with elevated blood pressure than in those without. No difference in carotid atherosclerosis prevalence was found in subjects bearing or not bearing components of the syndrome other than elevated blood pressure. The present findings demonstrate that subjects with MetS and elevated blood pressure have increased carotid atherosclerosis compared with subjects with MetS but without elevated blood pressure. The diagnosis of MetS per se might not adequately identify subjects at elevated cardiovascular risk.

Relation between atherogenic dyslipidemia and the Adult Treatment Program-III definition of metabolic syndrome (Genetic Epidemiology of Metabolic Syndrome Project)

Genetic Epidemiology of Metabolic Syndrome is a multinational, family-based study to explore the genetic basis of the metabolic syndrome. Atherogenic dyslipidemia (defined as low plasma high-density lipoprotein cholesterol with elevated triglycerides (<25th and >75th percentile for age, gender, and country, respectively) identified affected subjects for the metabolic syndrome. This report examines the frequency at which atherogenic dyslipidemia predicts the metabolic syndrome of the National Cholesterol Education Program Adult Treatment Panel III (ATP-III). One thousand four hundred thirty-six (854 men/582 women) affected patients by our criteria were compared with 1,672 (737 men/935 women) unaffected persons. Affected patients had more hypertension, obesity, and hyperglycemia, and they met a higher number of ATP-III criteria (3.2 +/- 1.1 SD vs 1.3 +/- 1.1 SD, p <0.001). Overall, 76% of affected persons also qualified for the ATP-III definition (Cohen's kappa 0.61, 95% confidence interval 0.59 to 0.64), similar to a separate group of 464 sporadic, unrelated cases (75%). Concordance increased from 41% to 82% and 88% for ages < or =35, 36 to 55, and > or =55 years, respectively. Affected status was also independently associated with waist circumference (p <0.001) and fasting glucose (p <0.001) but not systolic blood pressure (p = 0.43). Thus, the lipid-based criteria used to define affection status in this study substantially parallels the ATP-III definition of metabolic syndrome in subjects aged >35 years. In subjects aged <35 years, atherogenic dyslipidemia frequently occurs in the absence of other metabolic syndrome risk factors.

The metabolic syndrome in Chinese, Malays and Asian Indians. Factor analysis of data from the 1998 Singapore National Health Survey

We used factor analysis to define and compare the manner in which the various features of the metabolic syndrome are linked or clustered in Chinese, Malays and Asian Indians. One thousand nine hundred and fifty seven men (1324 Chinese, 391 Malays and 261 Asian Indians) and 2308 women (1622 Chinese, 391 Malays and 296 Asian Indians) were examined. Anthropometry, blood pressure, serum glucose, lipid concentrations, and serum insulin were measured for all subjects. These data were then subjected to factor analysis which reduced the variables examined to three factors in all ethnic groups and both genders. The first (dyslipidemia) factor was positively loaded for obesity, insulin resistance (IR), fasting triglyceride and negatively loaded for HDL-cholesterol. The second (hyperglycemia) factor was positively loaded for IR and blood glucose. The third (hypertension) factor was positively loaded for obesity and blood pressure. IR was positively loaded in the hypertension factor in Malay women but not in others. Rather than a single entity causally associated with insulin resistance (IR), our findings support a concept in which the metabolic syndrome represents several distinct entities (dyslipidemia, hypertension and hyperglycemia). It appears that Malay females may be more prone to develop hypertension in association with IR.

Insulin resistance syndrome in a representative sample of children and adolescents from Quebec, Canada

OBJECTIVES

To estimate the prevalence of insulin resistance syndrome (IRS) in a representative sample of youth. To test for the independent contribution of insulin resistance (IR) and adiposity to clustering of metabolic risk factors. To identify the underlying components of IRS. To examine the relationship between adiposity and fasting plasma levels of free fatty acids (FFA).

METHODS

In 1999, we conducted a school-based survey of a representative sample of youth aged 9, 13 and 16 y in Quebec, Canada. Age-specific questionnaire data, standardized clinical measurements and a fasting blood sample were available for 2244 subjects. Fasting insulin and HOMA were used as surrogate measures of IR.

RESULTS

In all age-sex groups, adiposity indices, blood pressure (BP), plasma glucose and triglycerides (TG) increased significantly with increasing insulin quartiles while HDL cholesterol (HDL-C) decreased. The overall prevalence of IRS defined as hyperinsulinaemia combined with two or more risk factors including overweight, high systolic BP, impaired fasting glucose, high TG and low HDL-C, was 11.5% (95% CI: 10.2-12.9). There were no significant differences in the prevalence of IRS across ages or between sexes. The independent contribution of adiposity to clustering of risk factors was stronger than that of fasting insulin (or HOMA-IR). Factor analysis revealed three factors (BMI/insulin/lipids, BMI/insulin/glucose and diastolic/systolic BP) consistent across ages suggesting that more than one pathophysiologic process underlies IRS. Although elevation of FFA might be in the causal pathway linking obesity to IR, we did not detect any consistent association between measures of fatness and fasting plasma FFA.

CONCLUSION

IRS is highly prevalent in youth, even among children as young as age 9 y. Factor analysis identifies three physiologic domains within IRS with a unifying role for markers of IR and adiposity.

What is the relationship between exercise and metabolic abnormalities? A review of the metabolic syndrome

Prevention of the metabolic syndrome and treatment of its main characteristics are now considered of utmost importance in order to combat the epidemic of type 2 diabetes mellitus and to reduce the increased risk of cardiovascular disease and all-cause mortality. Insulin resistance/hyperinsulinaemia are consistently linked with a clustering of multiple clinical and subclinical metabolic risk factors. It is now widely recognised that obesity (especially abdominal fat accumulation), hyperglycaemia, dyslipidaemia and hypertension are common metabolic traits that, concurrently, constitute the distinctive insulin resistance or metabolic syndrome. Cross-sectional and prospective data provide an emerging picture of associations of both physical activity habits and cardiorespiratory fitness with the metabolic syndrome. The metabolic syndrome, is a disorder that requires aggressive multi-factorial intervention. Recent treatment guidelines have emphasised the clinical utility of diagnosis and an important treatment role for 'therapeutic lifestyle change', incorporating moderate physical activity. Several previous narrative reviews have considered exercise training as an effective treatment for insulin resistance and other components of the syndrome. However, the evidence cited has been less consistent for exercise training effects on several metabolic syndrome variables, unless combined with appropriate dietary modifications to achieve weight loss. Recently published randomised controlled trial data concerning the effects of exercise training on separate metabolic syndrome traits are evaluated within this review. Novel systematic review and meta-analysis evidence is presented indicating that supervised, long-term, moderate to moderately vigorous intensity exercise training, in the absence of therapeutic weight loss, improves the dyslipidaemic profile by raising high density lipoprotein-cholesterol and lowering triglycerides in overweight and obese adults with characteristics of the metabolic syndrome. Lifestyle interventions, including exercise and dietary-induced weight loss may improve insulin resistance and glucose tolerance in obesity states and are highly effective in preventing or delaying the onset of type 2 diabetes in individuals with impaired glucose regulation. Randomised controlled trial evidence also indicates that exercise training decreases blood pressure in overweight/obese individuals with high normal blood pressure and hypertension. These evidence-based findings continue to support recommendations that supervised or partially supervised exercise training is an important initial adjunctive step in the treatment of individuals with the metabolic syndrome. Exercise training should be considered an essential part of 'therapeutic lifestyle change' and may concurrently improve insulin resistance and the entire cluster of metabolic risk factors.

The metabolic syndrome defined by factor analysis and incident type 2 diabetes in a chinese population with high postprandial glucose

OBJECTIVE

The aim of this study was to examine how the major components of the metabolic syndrome relate to each other and to the development of diabetes using factor analysis.

RESEARCH DESIGN AND METHODS

The screening survey for type 2 diabetes was conducted in 1994, and a follow-up study of nondiabetic individuals at baseline was carried out in 1999 in the Beijing area. Among 934 nondiabetic and 305 diabetic subjects at baseline, factor analysis was performed using the principle components analysis with varimax orthogonal rotation of continuously distributed variables considered to represent the components of the metabolic syndrome. Fasting insulin was used as a marker for insulin resistance. Of the 559 subjects without diabetes at baseline, 129 developed diabetes during the 5-year follow-up. Factors identified at baseline were used as independent variables in univariate and multivariate logistic regression models to determine risk factor clusters predicting the development of diabetes.

RESULTS

Four factors were identified in nondiabetic and diabetic subjects. Fasting insulin levels, BMI, and waist-to-hip ratio were associated with one factor. Systolic and diastolic blood pressures were associated with the second factor. Two-hour postload plasma glucose (2-h PG) and serum insulin and fasting plasma glucose were associated with the third factor. Serum total cholesterol and triglycerides were associated with the fourth factor. The first and the third factors predicted the development of diabetes. In diabetic patients at baseline, the combination of systolic and diastolic blood pressure was the most important factor, and urinary albumin excretion rate clustered with fasting and 2-h PG levels.

CONCLUSIONS

Insulin resistance alone does not underlie all features of the metabolic syndrome. Different physiological processes associated with various components of the metabolic syndrome contain unique information about diabetes risk. Microalbunuria is more likely to be a complication of type 2 diabetes or hypertension than a marker for the metabolic syndrome.

Factor analysis of the metabolic syndrome in spinal cord-injured men

Disturbances of carbohydrate and lipid metabolism in men with spinal cord injury are common, but poorly defined. Clustering of recognized risk factors for obesity and disorders of carbohydrate and lipid metabolism are characteristic of the metabolic syndrome. The purpose of this study was to investigate the presence of metabolic syndrome using modifications of the World Health Organization (WHO) definition and including total physical activity levels (minutes/week), in a group of active males with spinal cord injury who were carefully matched for age, height, and weight with active able-bodied males. Factor analysis is used widely to explore factors of the metabolic syndrome. This technique was used in this study of 20 spinal cord-injured (SCI) men and 20 able-bodied controls, matched for age, height, and weight. Three-factor models, each reflecting a different aspect of the metabolic syndrome, were identified for both study groups. The average communality score for the SCI group was 0.8 and 0.7 for the control group. For the SCI group, factor 1 reflected an interaction between adiposity measures, physical activity, and postload insulin and glucose, factor 2 was reflective of dyslipidemia, while factor 3 revealed an interaction between fasting levels of insulin and glucose. In the control group, factor 1 reflected an association between the adiposity measures and physical activity, factor 2 was reflective of postload glycemic control, with factor 3 reflecting an interaction between fasting insulin and dyslipidemia. By summation of the total variance of each factor, the 3-factor models explained 80% and 69% of the variance in the original 9 variables examined in the SCI and control groups, respectively. In summary, while the WHO definition for the metabolic syndrome appears suitable for use in identifying the incidence of this syndrome in SCI men, some modification of anthropometric and lipid measures may be required.

Cardiovascular risk factors and cognitive function in adults 30-59 years of age (NHANES III)

In the Third National Health and Nutrition Examination Survey (NHANES III), three measures of cognitive function [Simple Reaction Time Test (SRTT), Symbol Digit Substitution Test (SDST), and Serial Digit Learning Test (SDLT)] were administered to a half-sample of 3,385 adult men and nonpregnant women 30-59 years of age with no history of stroke. We used multiple linear regression analysis to determine whether there was an independent association between performance on each cognitive function measure and defined hypertension (HTN) alone, type 2 diabetes mellitus (DM) alone, and coexistent HTN and DM after adjustment for demographic and socioeconomic variables and selected health behaviors. After adjustment for the sociodemographic variables, the combination of HTN + DM, but not HTN alone or DM alone, was significantly associated with worse performance on the SRTT (p = 0.031) and the SDST (p = 0.011). A similar pattern was observed for SDLT performance, but the relationship did not reach statistical significance (p = 0.101). We conclude that HTN in combination with DM is associated with detectable cognitive decrements in persons under age 60.

Intra-abdominal fat is a major determinant of the National Cholesterol Education Program Adult Treatment Panel III criteria for the metabolic syndrome

The underlying pathophysiology of the metabolic syndrome is the subject of debate, with both insulin resistance and obesity considered as important factors. We evaluated the differential effects of insulin resistance and central body fat distribution in determining the metabolic syndrome as defined by the National Cholesterol Education Program (NCEP) Adult Treatment Panel III. In addition, we determined which NCEP criteria were associated with insulin resistance and central adiposity. The subjects, 218 healthy men (n = 89) and women (n = 129) with a broad range of age (26-75 years) and BMI (18.4-46.8 kg/m2), underwent quantification of the insulin sensitivity index (Si) and intra-abdominal fat (IAF) and subcutaneous fat (SCF) areas. The metabolic syndrome was present in 34 (15.6%) of subjects who had a lower Si [median: 3.13 vs. 6.09 x 10(-5) min(-1)/(pmol/l)] and higher IAF (166.3 vs. 79.1 cm2) and SCF (285.1 vs. 179.8 cm2) areas compared with subjects without the syndrome (P < 0.001). Multivariate models including Si, IAF, and SCF demonstrated that each parameter was associated with the syndrome. However, IAF was independently associated with all five of the metabolic syndrome criteria. In multivariable models containing the criteria as covariates, waist circumference and triglyceride levels were independently associated with Si and IAF and SCF areas (P < 0.001). Although insulin resistance and central body fat are both associated with the metabolic syndrome, IAF is independently associated with all of the criteria, suggesting that it may have a pathophysiological role. Of the NCEP criteria, waist circumference and triglycerides may best identify insulin resistance and visceral adiposity in individuals with a fasting plasma glucose <6.4 mmol/l.

Obesity and high blood pressure: a clinical phenotype for the insulin resistance syndrome in African Americans

The high prevalence of insulin resistance syndrome in African Americans predisposes this population to higher morbidity and mortality from cardiovascular disease. To test the hypothesis that the combination of obesity and high blood pressure (BP) represents the physical phenotype of insulin resistance syndrome, 337 African-American men and women aged 32+/-4 years were examined and classified into four groups (nonobese-normal BP, nonobese-high BP, obese-normal BP, obese-high BP), according to presence or absence of obesity and high BP. Mean values of glucose, insulin, lipids, urinary albumin excretion, and clamp-derived insulin sensitivity were determined for each group. Prevalence of prediabetes (24.4%), diabetes (19.2%), and insulin resistance syndrome (87.2%) were highest in the obese-high BP group (p<0.001). Mean triglycerides, urinary albumin excretion, fasting glucose, fasting insulin, and insulin resistance were highest in the obese-high BP group (p<0.001). Subjects with both obesity and high BP showed greater expression of lipid and glucose abnormalities, higher urinary albumin excretion, and greater prevalence of prediabetes, undetected type 2 diabetes, and insulin resistance syndrome.

Metabolic and inflammation variable clusters and prediction of type 2 diabetes: factor analysis using directly measured insulin sensitivity

Factor analysis, a multivariate correlation technique, has been used to provide insight into the underlying structure of the metabolic syndrome. The majority of previous factor analyses, however, have used only surrogate measures of insulin sensitivity; very few have included nontraditional cardiovascular disease (CVD) risk factors such as plasminogen activator inhibitor (PAI)-1, fibrinogen, and C-reactive protein (CRP); and only a limited number have assessed the ability of factors to predict type 2 diabetes. The objective of this study was to investigate, using factor analysis, the clustering of metabolic and inflammation variables using data from 1,087 nondiabetic participants in the Insulin Resistance Atherosclerosis Study (IRAS) and to determine the association of these clusters with risk of type 2 diabetes at follow-up. This study includes information on directly measured insulin sensitivity (S(i)) from the frequently sampled intravenous glucose tolerance test among African-American, Hispanic, and non-Hispanic white subjects aged 40-69 years. Principal factor analysis of data from nondiabetic subjects at baseline (1992-1994) identified three factors, which explained 28.4, 7.4, and 6% of the total variance in the dataset, respectively. Based on factor loadings of >or= 0.40, these factors were interpreted as 1) a "metabolic" factor, with positive loadings of BMI, waist circumference, 2-h glucose, log triglyceride, and log PAI-1 and inverse loadings of log S(i) + 1 and HDL; 2) an "inflammation" factor, with positive loadings of BMI, waist circumference, fibrinogen, and log CRP and an inverse loading of log S(i) + 1; and 3) a "blood pressure" factor, with positive loadings of systolic and diastolic blood pressure. The results were similar within strata of ethnicity, and there were only subtle differences in sex-specific analyses. In a prospective analysis, each of the factors was a significant predictor of diabetes after a median follow-up period of 5.2 years, and each factor remained significant in a multivariate model that included all three factors, although this three-factor model was not significantly more predictive than models using either impaired glucose tolerance or conventional CVD risk factors. Factor analysis identified three underlying factors among a group of inflammation and metabolic syndrome variables, with insulin sensitivity loading on both the metabolic and inflammation variable clusters. Each factor significantly predicted diabetes in multivariate analysis. The findings support the emerging hypothesis that chronic subclinical inflammation is associated with insulin resistance and comprises a component of the metabolic syndrome.